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1.发明公开公开(公告)号：US20230153337A1
公开(公告)日：2023-05-18
申请号：US18157452
申请日：2023-01-20
Inventor： Wenbin JIANG , Yajuan LV , Chunguang CHAI , Yong ZHU
IPC: G06F16/332 , G06F40/30
CPC classification number: G06F16/3329 , G06F40/30
Abstract: A question answering method, a method of training a question answering model, a device, and a medium are provided, which relate to a field of artificial intelligence technology, in particular to fields of natural language processing technology, deep learning technology, and knowledge mapping technology. The question answering method includes: obtaining data to be processed, wherein the data to be processed includes a question and candidate answers; performing general semantic understanding on the data to be processed to obtain a general data feature; selecting a target question answering mode from candidate question answering modes based on the general data feature; and processing the general data feature by using the target question answering mode, to obtain a target answer for the question from the candidate answers.
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2.发明申请公开(公告)号：US20230013796A1
公开(公告)日：2023-01-19
申请号：US17866104
申请日：2022-07-15
Inventor： Wenbin JIANG , Zhifan FENG , Xinwei FENG , Yajuan LYU , Yong ZHU
Abstract: The present disclosure provides a method and apparatus for acquiring a pre-trained model, an electronic device and a storage medium, and relates to the fields such as deep learning, natural language processing, knowledge graph and intelligent voice. The method may include: acquiring a pre-training task set composed of M pre-training tasks, M being a positive integer greater than 1, the pre-training tasks including: N question-answering tasks corresponding to different question-answering forms, N being a positive integer greater than 1 and less than or equal to M; and jointly pre-training the pre-trained model according to the M pre-training tasks.
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公开(公告)号：US20230008897A1
公开(公告)日：2023-01-12
申请号：US17932598
申请日：2022-09-15
Inventor： Wenbin JIANG , Yajuan LYU , Yong ZHU , Hua WU , Haifeng WANG
IPC: G06F16/735
Abstract: An information search method includes: obtaining search words at least including a question to be searched and obtaining an initial text vector representation of the search words; obtaining a video corresponding to the search words, and obtaining multi-modality vector representations of the video; starting from the initial text vector representation, performing N rounds of interaction between the video and the search words based on the multi-modality vector representations and a text vector representation of the search words of a current round, to generate a target fusion vector representation, where N is an integer greater than or equal to 1; and obtaining target video frames matching the question to be searched by annotating the video based on the target fusion vector representation.
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4.发明公开公开(公告)号：US20230214688A1
公开(公告)日：2023-07-06
申请号：US18119494
申请日：2023-03-09
Inventor： Jiyuan ZHANG , Jianguo MAO , Zengfeng ZENG , Weihua PENG , Wenbin JIANG , Yajuan LYU
IPC: G06N5/04
CPC classification number: G06N5/04
Abstract: A method and apparatus for determining an answer to a question are provided. The method includes: splicing an acquired to-be-queried question with each candidate answer into each question-answer pair; performing reasoning operations of feature combination parameters on different granularity features of each question-answer pair at a preset number of steps in a horizontal direction based on recurrent characteristics of a recurrent neural network; determining feature combination weights of the different granularity features using multiple preset vertical reasoning layers at different reasoning focuses respectively, at each step of the reasoning operations in the horizontal direction; obtaining a candidate answer feature corresponding to each question-answer pair, respectively, through a final step of the reasoning operations; and determining a target candidate answer matching the to-be-queried question based on a feature similarity between a question feature of the to-be-queried question and each candidate answer feature.
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Patent Agency Ranking
5.发明申请公开(公告)号：US20230092736A1
公开(公告)日：2023-03-23
申请号：US17872318
申请日：2022-07-25
Inventor： Wenbin JIANG , Yajuan LYU , Yong ZHU , Hua WU , Haifeng WANG
Abstract: The present disclosure provides a method for processing intelligent question-answering, an intelligent question-answering system, an electronic device and a storage medium, and relates to the field of artificial intelligence technologies, such as machine learning technologies, natural language processing technologies, or the like. An implementation includes: acquiring an input question and input data information; and based on the question, the data information and a plurality of knowledge bases, deciding an answer to the question by multilayer appreciation using a plurality of understanding module layers.
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公开(公告)号：US20230086145A1
公开(公告)日：2023-03-23
申请号：US17936761
申请日：2022-09-29
Inventor： Wenbin JIANG , Yajuan LV , Yong ZHU , Hua WU , Haifeng WANG
IPC: G06F16/738 , G06N5/02
Abstract: A method of processing data, a device, and a medium are provided, which relate to a field of an artificial intelligence technology, in particular to fields of computer vision, natural language technology, speech technology, deep learning and knowledge graph. The method of processing data includes: generating a video feature, a question feature and an answer feature based on acquired video data, acquired question data and acquired candidate answer data; determining a link relationship between the video feature, the question feature and the answer feature; and determining a matching result for the video data, the question data and the candidate answer data based on the link relationship.
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公开(公告)号：US20230018489A1
公开(公告)日：2023-01-19
申请号：US17862519
申请日：2022-07-12
Inventor： Wenbin JIANG , Yajuan LYU , Yong ZHU , Hua WU , Haifeng WANG
IPC: G06F16/242 , G06F16/21 , G06F16/245 , G06N5/02
Abstract: The present disclosure discloses a method for acquiring a structured question-answering (QA) model, a QA method and corresponding apparatuses, and relates to knowledge graph and deep learning technologies in the field of artificial intelligence technologies. A specific implementation solution involves: acquiring training samples corresponding to N structured QA database types, the training samples including question samples, information of the structured QA database types and query instruction samples used by the question samples to query structured QA databases of the types, N being an integer greater than 1; and training a text generation model by using the training samples to obtain the structured QA model, wherein the question samples and the information of the structured QA database types are taken as input to the text generation model, and the query instruction samples are taken as target output of the text generation model.
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公开(公告)号：US20220391426A1
公开(公告)日：2022-12-08
申请号：US17820285
申请日：2022-08-17
Inventor： Xinwei FENG , Meng TIAN , Feifei LI , Hongjian SHI , Wenbin JIANG , Xueqian WU , Chenyang GUO , Yu WANG , Yu SUN , Shuaiyu CHEN
IPC: G06F16/332 , G06F16/2455 , G06F40/30
Abstract: The present disclosure provides a multi-system-based intelligent question answering method and apparatus, and a device, relating to the field of artificial intelligence, in particular to the field of knowledge graph. The specific implementation solution is: determining a question category of question information in response to a question answering instruction of a user, wherein the question answering instruction is used to indicate the question information; determining a query engine corresponding to the question category, and invoking multiple question analysis systems corresponding to the query engine according to the query engine; and feeding back answer information to the user when the answer information corresponding to the question information is determined according to a current question analysis system in a process of processing the question information by sequentially using the multiple question analysis systems according to system priorities of the question analysis systems.
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公开(公告)号：US20210192364A1
公开(公告)日：2021-06-24
申请号：US17124030
申请日：2020-12-16
Inventor： Haifeng WANG , Wenbin JIANG , Yajuan LV , Yong ZHU , Hua WU
IPC: G06N5/02 , G06F40/30 , G06F40/279 , G06K9/62
Abstract: The present application discloses a text processing method and device based on natural language processing and a knowledge graph, and relates to the in-depth field of artificial intelligence technology. A specific implementation is: an electronic device uses a joint learning model to obtain a semantic representation, which is obtained by the joint learning model by combining knowledge graph representation learning and natural language representation learning, it combines a knowledge graph representation learning and a natural language representation learning, compared to using only the knowledge graph representation learning or the natural language representation learning to learn semantic representation of a prediction object, factors considered by the joint learning model are more in quantity and comprehensiveness, so accuracy of semantic representation can be improved, and thus accuracy of text processing can be improved.
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